A stochastic approach for quantifying immigrant integration: the Spanish test case
Elena Agliari, Adriano Barra, Pierluigi Contucci, Rickard Sandell,, Cecilia Vernia

TL;DR
This paper introduces a stochastic process framework to analyze immigrant integration in Spain, revealing different diffusion behaviors for social and economic quantifiers and enabling predictive scenarios for policy planning.
Contribution
It applies stochastic process theory to immigration data, providing novel insights into integration dynamics and forecasting capabilities at local levels.
Findings
Social integration follows pure diffusion dynamics.
Economic integration exhibits ballistic behavior.
Forecasting scenarios highlight local fluctuations and policy implications.
Abstract
We apply stochastic process theory to the analysis of immigrant integration. Using a unique and detailed data set from Spain, we study the relationship between local immigrant density and two social and two economic immigration quantifiers for the period 1999-2010. As opposed to the classic time-series approach, by letting immigrant density play the role of "time", and the quantifier the role of "space" it become possible to analyze the behavior of the quantifiers by means of continuous time random walks. Two classes of results are obtained. First we show that social integration quantifiers evolve following pure diffusion law, while the evolution of economic quantifiers exhibit ballistic dynamics. Second we make predictions of best and worst case scenarios taking into account large local fluctuations. Our stochastic process approach to integration lends itself to interesting forecasting…
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